Created 22.11.2023
Updated 22.11.2023

A recent study conducted at LUT, How to succeed with an AI-first strategy, systematically outlines how companies can formulate AI-centric strategies from various perspectives, thus integrating artificial intelligence into the core of their business.

The research demonstrates how AI algorithms redefine products and services, enhance user experiences, and contribute to automate decisions related to essential business operations.

"AI clearly plays a strategic role both at the core of business processes and in creating customer value in so-called AI-first companies," explains Professor Paavo Ritala from LUT Business School.

For instance, General Electric (GE) saved $80 million annually by optimizing debts and receivables, JP Morgan Chase reduced 360,000 hours of routine legal and financial tasks, and PayPal minimized transaction fraud to just 0.32% of its revenue. All these efficiency gains were achieved through the utilization of artificial intelligence in business processes.

The study identifies three distinct AI-first strategies based on companies' starting points: Digital Tycoon, Niche Carver, and Asset Augmenter. These strategies reflect the diverse approaches companies can adopt to leverage AI effectively and gain a competitive edge in their respective industries.

AI-first strategies

  • Digital Tycoons: process massive datasets, orchestrate digital platforms, and benefit from the synergy of increasing data volumes, user growth, and advancements in AI development. They utilize algorithms, among other things, to enhance customer experiences and to continuously improve their digital offerings. Their challenges include regulatory pressures in the industry and reputation risks, as they grow in size and power. Example companies include Google and Meta (formerly Facebook).
  • Niche Carvers: focus on utilizing data in a specific industry and develop superior AI algorithms in domains, such as medical imaging or speech recognition. Competitiveness is based on the algorithms' superior performance in the field in question. Challenges include scaling the business and demonstrating added value to customers. Example companies include Speechly and HeadAI.
  • Asset Augmenters: operate in traditional fields such as industrial manufacturing and retail and use AI applications to take advantage of the unique real-time data from their own operations and devices. Their challenges include the burden of old legacy and practices and potential skepticism towards AI among employees or customers. Example companies include Siemens and John Deere.

A strategy revolving around AI – worthwhile or not?

According to the study, integrating artificial intelligence into the core of business is not exclusive to digital giants like Google; rather, AI is a versatile technology with strategic significance and measurable benefits across various industries.

However, the number of AI-first companies remains relatively small. AI has more commonly been utilized in pilots and individual use cases rather than throughout entire organizations and operations.

"Artificial intelligence has become a popular marketing term for many software companies, making its strategic significance difficult to assess. Nevertheless, we argue that AI will play an increasingly crucial strategic role in companies," says Industry Professor Mika Ruokonen from LUT Business School.

The current AI craze may tempt companies to place AI at the center of their strategy even though customers have traditionally held that position – that might lead to misguided strategic choices and focuses.

"Having AI at the core of the strategy may not necessarily be only beneficial. AI-first companies face the challenge of defining what their strategy is all about. An AI-first strategy may not be suitable for all businesses. Our research provides tools for companies to choose their own path and approach. We also identify the most common risks associated with each strategy," Ruokonen explains.

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